Revisiting multi-channel communication to mitigate interference and link dynamics in wireless sensor networks

Multichannel communication has been proposed as alternative to adaptive (single-channel) routing protocols for mitigating the impact of interference and link dynamics in wireless sensor networks. While several studies have advocated features of both techniques (not without running up against contradicting arguments) a comprehensive study that aligns these results is still lacking. This paper aims at filling this gap. We present an experimental test bed setup used to perform extensive measurements for both single-channel and multichannel communication. We first analyze single-channel and multichannel communication over a single-hop in terms of packet reception ratio, maximum burst loss, temporal correlation of losses, and loss correlations across channels. Results show that multichannel communication with channel hopping significantly reduces link burstiness and packet loss correlation. For multi-hop networks, multi-channel communication and adaptive routing show similar end-to-end reliability in dense topologies, while multichannel communication can outperform adaptive routing in sparse networks with bursty links

Wireless information and power transfer: from scientific hypothesis to engineering practice

Recently, there has been substantial research interest in the subject of Simultaneous Wireless Information andPower Transfer (SWIPT) owing to its cross-disciplinary appeal and its wide-ranging application potential, whichmotivates this overview. More explicitly, we provide a brief survey of the state-of-the-art and introduce severalpractical transceiver architectures that may facilitate its implementation. Moreover, the most important link-levelas well as system-level design aspects are elaborated on, along with a variety of potential solutions and researchideas. We envision that the dual interpretation of Radio Frequency (RF) signals creates new opportunities as wellas challenges requiring substantial research, innovation and engineering efforts

Impacts of Soil Type and Moisture on the Capacity of Multi-Carrier Modulation in Internet of Underground Things

Unique interactions between soil and communication components in wireless underground communications necessitate revisiting fundamental communication concepts from a different perspective. In this paper, capacity profile of wireless underground (UG) channel for multi-carrier transmission techniques is analyzed based on empirical antenna return loss and channel frequency response models in different soil types and moisture values. It is shown that data rates in excess of 124 Mbps are possible for distances up to 12 m. For shorter distances and lower soil moisture conditions, data rates of 362 Mbps can be achieved. It is also shown that due to soil moisture variations, UG channel experiences significant variations in antenna bandwidth and coherence bandwidth, which demands dynamic subcarrier operation. Theoretical analysis based on this empirical data show that by adaption to soil moisture variations, 180% improvement in channel capacity is possible when soil moisture decreases. It is shown that compared to a fixed bandwidth system; soilbased, system and sub-carrier bandwidth adaptation leads to capacity gains of 56%-136%. The analysis is based on indoor and outdoor experiments with more than 1; 500 measurements taken over a period of 10 months. These semi-empirical capacity results provide further evidence on the potential of underground channel as a viable media for high data rate communication and highlight potential improvements in this area

Impacts of Soil Type and Moisture on the Capacity of Multi-Carrier Modulation in Internet of Underground Things

Unique interactions between soil and communication components in wireless underground communications necessitate revisiting fundamental communication concepts from a different perspective. In this paper, capacity profile of wireless underground (UG) channel for multi-carrier transmission techniques is analyzed based on empirical antenna return loss and channel frequency response models in different soil types and moisture values. It is shown that data rates in excess of 124 Mbps are possible for distances up to 12 m. For shorter distances and lower soil moisture conditions, data rates of 362 Mbps can be achieved. It is also shown that due to soil moisture variations, UG channel experiences significant variations in antenna bandwidth and coherence bandwidth, which demands dynamic subcarrier operation. Theoretical analysis based on this empirical data show that by adaption to soil moisture variations, 180% improvement in channel capacity is possible when soil moisture decreases. It is shown that compared to a fixed bandwidth system; soilbased, system and sub-carrier bandwidth adaptation leads to capacity gains of 56%-136%. The analysis is based on indoor and outdoor experiments with more than 1; 500 measurements taken over a period of 10 months. These semi-empirical capacity results provide further evidence on the potential of underground channel as a viable media for high data rate communication and highlight potential improvements in this area

A Socio-inspired CALM Approach to Channel Assignment Performance Prediction and WMN Capacity Estimation

A significant amount of research literature is dedicated to interference mitigation in Wireless Mesh Networks (WMNs), with a special emphasis on designing channel allocation (CA) schemes which alleviate the impact of interference on WMN performance. But having countless CA schemes at one's disposal makes the task of choosing a suitable CA for a given WMN extremely tedious and time consuming. In this work, we propose a new interference estimation and CA performance prediction algorithm called CALM, which is inspired by social theory. We borrow the sociological idea of a "sui generis" social reality, and apply it to WMNs with significant success. To achieve this, we devise a novel Sociological Idea Borrowing Mechanism that facilitates easy operationalization of sociological concepts in other domains. Further, we formulate a heuristic Mixed Integer Programming (MIP) model called NETCAP which makes use of link quality estimates generated by CALM to offer a reliable framework for network capacity prediction. We demonstrate the efficacy of CALM by evaluating its theoretical estimates against experimental data obtained through exhaustive simulations on ns-3 802.11g environment, for a comprehensive CA test-set of forty CA schemes. We compare CALM with three existing interference estimation metrics, and demonstrate that it is consistently more reliable. CALM boasts of accuracy of over 90% in performance testing, and in stress testing too it achieves an accuracy of 88%, while the accuracy of other metrics drops to under 75%. It reduces errors in CA performance prediction by as much as 75% when compared to other metrics. Finally, we validate the expected network capacity estimates generated by NETCAP, and show that they are quite accurate, deviating by as low as 6.4% on an average when compared to experimentally recorded results in performance testing

Energy efficient wireless sensor network protocols for monitoring and prognostics of large scale systems

In this work, energy-efficient protocols for wireless sensor networks (WSN) with applications to prognostics are investigated. Both analytical methods and verification are shown for the proposed methods via either hardware experiments or simulation. This work is presented in five papers. Energy-efficiency methods for WSN include distributed algorithms for i) optimal routing, ii) adaptive scheduling, iii) adaptive transmission power and data-rate control --Abstract, page iv